Comparison of Different Risk Classification Systems in 558 Patients with Gastrointestinal Stromal Tumors after R0-Resection

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Background: Due to adjuvant treatment concepts for patients with R0-resected gastrointestinal stromal tumors (GIST), a reproducible and reliable risk classification system proved of utmost importance for optimal treatment of patients and prediction of prognosis. The aim of this study was to reevaluate the impact of five widely-applied and well-established GIST risk classification systems (i.e. scores by Fletcher, Miettinen, Huang, Joensuu and TNM classification) on a series of 558 GIST patients with long-term follow-up after R0 resection. Methods: Tumor size, mitotic count and site were used in variable combination to predict high- and low risk patients by the use of the five risk classification models. For survival analyses disease-specific survival, disease-free survival and overall-survival were investigated. Patients with initial metastatic disease or incompletely resectable tumors were excluded. Results: All GIST classification models distinguished well between patients with high-risk and low-risk tumors and none of the five risk systems was superior to predict patient outcome. The models showed significant heterogeneity. There was no significant difference between the different risk-groups regarding overall-survival. Subdivision of GIST patients with very low- and low-risk appeared to be negligible. Conclusions: Currently applied GIST risk classification systems are comparable to predict high- or low-risk patients with initial non-metastatic and completely resected GIST. However, the heterogeneity of the high-risk group and the absence of differences in overall survival indicate the need for more precise tumor- and patient-related criteria for better stratification of GIST and identification of patients who would benefit best from adjuvant tyrosine kinase inhibitor therapy.

This publication has 57 references indexed in Scilit: